Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

6 June 2015

Papers citing "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"

50 / 1,102 papers shown

Title
Universal Dependency Parsing from Scratch Peng Qi Timothy Dozat Yuhao Zhang Christopher D. Manning 15 267 0 29 Jan 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 26 853 0 18 Jan 2019
Input Prioritization for Testing Neural Networks Taejoon Byun Vaibhav Sharma Abhishek Vijayakumar Sanjai Rayadurgam D. Cofer AAML 19 67 0 11 Jan 2019
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning Peter F. Schulam S. Saria OOD 16 103 0 02 Jan 2019
Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams Mohammad Kachuee Orpaz Goldstein Kimmo Karkkainen Sajad Darabi Majid Sarrafzadeh OOD 17 31 0 02 Jan 2019
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 10 550 0 13 Dec 2018
Scene Recomposition by Learning-based ICP Hamid Izadinia S. M. Seitz 3DV 3DPC 12 14 0 13 Dec 2018
Neural Processes Mixed-Effect Models for Deep Normative Modeling of Clinical Neuroimaging Data S. M. Kia A. Marquand 14 25 0 12 Dec 2018
Guided Dropout Rohit Keshari Richa Singh Mayank Vatsa BDL 13 37 0 10 Dec 2018
Physics-informed deep generative models Yibo Yang P. Perdikaris AI4CE PINN 11 57 0 09 Dec 2018
Backdooring Convolutional Neural Networks via Targeted Weight Perturbations Jacob Dumford Walter J. Scheirer AAML 6 116 0 07 Dec 2018
Random Spiking and Systematic Evaluation of Defenses Against Adversarial Examples Huangyi Ge Sze Yiu Chau Bruno Ribeiro Ninghui Li AAML 14 1 0 05 Dec 2018
Knowing what you know in brain segmentation using Bayesian deep neural networks Patrick McClure Nao Rho J. Lee Jakub R. Kaczmarzyk C. Zheng Satrajit S. Ghosh D. Nielson Adam G. Thomas P. Bandettini Francisco Pereira UQCV 3DV BDL 11 52 0 03 Dec 2018
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification Qi Lei Lingfei Wu Pin-Yu Chen A. Dimakis Inderjit S. Dhillon Michael Witbrock AAML 13 92 0 01 Dec 2018
Evaluating Bayesian Deep Learning Methods for Semantic Segmentation Jishnu Mukhoti Y. Gal UQCV BDL 29 220 0 30 Nov 2018
Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer Vision M. Joneidi Alireza Zaeemzadeh Nazanin Rahnavard M. Shah 22 13 0 29 Nov 2018
Bayesian graph convolutional neural networks for semi-supervised classification Yingxue Zhang Soumyasundar Pal Mark J. Coates Deniz Üstebay GNN BDL 19 227 0 27 Nov 2018
Probabilistic Object Detection: Definition and Evaluation David Hall Feras Dayoub John Skinner Haoyang Zhang Dimity Miller Peter Corke G. Carneiro A. Angelova Niko Sünderhauf UQCV 24 111 0 27 Nov 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 20 392 0 19 Nov 2018
Uncertain Trees: Dealing with Uncertain Inputs in Regression Trees Myriam Tami Marianne Clausel Emilie Devijver A. Dulac Éric Gaussier Stefan Janaqi M. Chèbre UQCV 11 0 0 27 Oct 2018
CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation Radek Mackowiak Philip Lenz Omair Ghori Ferran Diego O. Lange Carsten Rother 26 108 0 23 Oct 2018
Good Initializations of Variational Bayes for Deep Models Simone Rossi Pietro Michiardi Maurizio Filippone BDL 17 21 0 18 Oct 2018
PANDA: AdaPtive Noisy Data Augmentation for Regularization of Undirected Graphical Models Yinan Li Xiao Liu Fang Liu 21 7 0 11 Oct 2018
Deterministic Variational Inference for Robust Bayesian Neural Networks Anqi Wu Sebastian Nowozin Edward Meeds Richard E. Turner José Miguel Hernández-Lobato Alexander L. Gaunt UQCV AAML BDL 29 16 0 09 Oct 2018
Design by adaptive sampling David H. Brookes Jennifer Listgarten TPM 31 65 0 08 Oct 2018
Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods Apratim Bhattacharyya Mario Fritz Bernt Schiele UQCV 17 46 0 01 Oct 2018
Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI Jörg Sander B. D. de Vos J. Wolterink Ivana Išgum 9 59 0 27 Sep 2018
Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection Dimity Miller Feras Dayoub Michael Milford Niko Sünderhauf 12 105 0 17 Sep 2018
A Full End-to-End Semantic Role Labeler, Syntax-agnostic Over Syntax-aware? Jiaxun Cai Shexia He Z. Li Zhao Hai 27 77 0 11 Aug 2018
Policy Optimization as Wasserstein Gradient Flows Ruiyi Zhang Changyou Chen Chunyuan Li Lawrence Carin 9 66 0 09 Aug 2018
Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy Firat Özdemir Z. Peng C. Tanner Philipp Fürnstahl O. Goksel 12 28 0 18 Jul 2018
Practical Obstacles to Deploying Active Learning David Lowell Zachary Chase Lipton Byron C. Wallace 25 111 0 12 Jul 2018
Machine Learning in High Energy Physics Community White Paper K. Albertsson Piero Altoe D. Anderson John R. Anderson Michael Andrews ... Michael Williams Wenjing Wu Stefan Wunsch Kun Yang O. Zapata AI4CE 6 220 0 08 Jul 2018
A survey on policy search algorithms for learning robot controllers in a handful of trials Konstantinos Chatzilygeroudis Vassilis Vassiliades F. Stulp Sylvain Calinon Jean-Baptiste Mouret 15 154 0 06 Jul 2018
Simpler but More Accurate Semantic Dependency Parsing Timothy Dozat Christopher D. Manning GNN 13 177 0 03 Jul 2018
Dropout-based Active Learning for Regression Evgenii Tsymbalov Maxim Panov Alexander Shapeev BDL UQCV 6 56 0 26 Jun 2018
Understanding Dropout as an Optimization Trick Sangchul Hahn Heeyoul Choi ODL 11 34 0 26 Jun 2018
On the Implicit Bias of Dropout Poorya Mianjy R. Arora René Vidal 17 66 0 26 Jun 2018
Towards safe deep learning: accurately quantifying biomarker uncertainty in neural network predictions Zach Eaton-Rosen Felix J. S. Bragman Sotirios Bisdas Sebastien Ourselin M. Jorge Cardoso UQCV 15 85 0 22 Jun 2018
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors S. Ghosh Jiayu Yao Finale Doshi-Velez BDL UQCV 13 77 0 13 Jun 2018
Meta-Learning for Stochastic Gradient MCMC Wenbo Gong Yingzhen Li José Miguel Hernández-Lobato BDL 16 44 0 12 Jun 2018
Randomized Prior Functions for Deep Reinforcement Learning Ian Osband John Aslanides Albin Cassirer UQCV BDL 4 373 0 08 Jun 2018
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 17 68 0 06 Jun 2018
MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images S. Graham Hao Chen Jevgenij Gamper Qi Dou Pheng-Ann Heng David R. J. Snead Yee Wah Tsang Nasir M. Rajpoot MedIm 19 301 0 05 Jun 2018
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 29 951 0 05 Jun 2018
Learn the new, keep the old: Extending pretrained models with new anatomy and images Firat Özdemir Philipp Fürnstahl Orçun Göksel CLL 20 48 0 01 Jun 2018
Short-term Load Forecasting with Deep Residual Networks Kunjin Chen Kunlong Chen Qin Wang Ziyu He Jun Hu Jinliang He 27 463 0 30 May 2018
To Trust Or Not To Trust A Classifier Heinrich Jiang Been Kim Melody Y. Guan Maya R. Gupta UQCV 17 464 0 30 May 2018
Lightweight Probabilistic Deep Networks Jochen Gast Stefan Roth UQCV OOD BDL 22 180 0 29 May 2018
Towards Robust Evaluations of Continual Learning Sebastian Farquhar Y. Gal CLL 13 304 0 24 May 2018